Data’s Ethical Landmines

There has been a lot of hype around the introduction of social media data and big data to the worlds of data integration and master data management. After all, isn’t more data  capable of helping us identify and understand our customers better  invaluable to the business? Perhaps, but along with its infinite value could come some highly unexpected, extensive costs and liabilities if not handled appropriately.

As we integrate external data sources we are typically aware of compliance rules and regulations. But, if not defined by a specific governing body, we may overlook the data management practices that strike the nervous chords of our target populations. We are consistently seeing more news reports about brand-damaging situations companies are facing because the ethical implications of their actions were just not considered.

Why are we overlooking what should be so obvious? Here are some of the issues companies integrating master data are tripping over:

1. Morals influence values. Our customer’s values are influenced by their morals. But companies are not human (duh, right?). Business values are not morally based, rather they are defined in corporate meetings driven by two things: profit and innovation.

3. Ethics are the reflection of the decisions and actions we make based on our values. Our customers evaluate and react to our corporate decisions and actions based on their values. It is important to note that ethics by their derived nature are not individually defined but more a reflection of the social codes of a given group, culture, or society.

4. Data is ethically neutral. (Davis and Patterson. 2012. Ethics of Big Data. Sebastopol: O’Reilly). The use of data is NOT ethically neutral. How we, as organizations, collect, use, manage and distribute data will consistently be evaluated by our customers based on their values (not our business values) as to whether our corporate data decisions are ethical or not.

Managers of both the business and IT sides of the house need not only be aware of ethical dilemmas but be prepared to change behaviors to mitigate the risks they present. For companies challenged with regulatory requirements, financial audits, or security audits that might only have one shot at a data integration effort, here are some tactics that have worked:

1. Clearly identify your core organizational values. Be transparent with these values in all internal and external communications.

2. Assess and maintain keen awareness of your target market’s customer values. This can be a quickly moving target so evaluate regularly and often.

3. Perform regular audits of your data handling processes to ensure your business actions are in fact aligned with your stated company values. Data handling processes should be evaluated in regards to both actual actions and perceived actions  how do your customers perceive your data handling procedures. Make sure to evaluate all four areas of the data life cycle: collection, use, management and distribution.

4. COMMUNICATE! Communication internally and externally is imperative. Internal communication should be consistent, authentic, and always reflect company values. The more employees hear organization values and see them in action, the more likely their actions will follow suit. External communication should be frequent, concise, and transparent. Do not rely on your organization’s written privacy policy to communicate your values and ethical behaviors. Optimize social media and other communication channels to let your target market know you understand what they value and consistently seek to ensure your organizations actions are aligned with such values.

The answer to the question is yes  having more data that is capable of helping identify and understand our customers is invaluable to the business. This data is also extremely valuable to our customers and we must treat it with the respect they expect based on their values and not on the values of our organizations.